Indigenous-led toxic tours opening pathways for (re)connecting to place, people and all creation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Home to nine Tribal Nations, the northeastern corner of Oklahoma (US) is a place of immense resilience, cultural beauty and attachment to place. Horrifically, however, this same area is also home to massive environmental assaults that have occurred as a result of decades of lead and zinc mining. The improperly managed mine waste that has accumulated since the late 1800s now severely contaminates the water, land and air, having adverse impacts on the health of the ecosystem and the local human community alike. Leading the fight for cleanup and support of place and people since 1997 is the non-profit organisation called Local Environmental Action Demanded (LEAD Agency). One of LEAD’s primary tools for education and advocacy has been leading toxic tours across these harmed lands and waters. This contribution draws upon the nearly three decades of toxic tours that Rebecca and Earl have led by sharing key stories and experiences of important sites visited along the way, offering a snapshot of toxic tour experience. Drawing on Indigenous storywork and autoethnographic methodologies, this contribution aims to spotlight the potential of Indigenous-led toxic tours for helping to (re)connect people — both locals and visitors — to place and a responsibility of stewardship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it